library(eRm)
# Wald test on item level (z-values):
# z-statistic p-value
# beta V06 2.115 0.034
# beta V07 -0.934 0.350
# beta V08 -0.660 0.509
# test fits criteria, but eRm excludes items due to inappropriate response
# patterns within subgroups
# empty list is returned
data(ADL)
testthat::test_that("test_waldtest: inapprpriate response patterns",{
testthat::expect_equal(length(exhaustiveRasch::test_waldtest(items=1:5,
dset=ADL, na.rm=TRUE,
modelType="RM",
bonf=TRUE,
estimation_param=
estimation_control(est="eRm"))),
expected=0)})
#Wald test on item level (z-values):
# z-statistic p-value
# beta V12 -0.169 0.866
# beta V22 0.391 0.696
# beta V27 0.488 0.626
# beta V36 -0.645 0.519
# beta V39 -0.128 0.899
# list of 3 is returned (item combinations, fit rasch model and ppar)
data(ADL)
testthat::test_that("test_waldtest: lowest p-value=0.519",{
testthat::expect_equal(length(
exhaustiveRasch::test_waldtest(items=c(6,7,12,14,15), dset=ADL, na.rm=TRUE,
modelType="RM", bonf=FALSE,
estimation_param=
estimation_control(est="psychotools"))),
expected=3)})
# list of 3 is returned (item combinations, fit rasch model and ppar)
data(ADL)
testthat::test_that("test_waldtest: lowest p-value=0.519; na.rm=FALSE",{
testthat::expect_equal(length(
exhaustiveRasch::test_waldtest(items=c(6,7,12,14,15), dset=ADL, na.rm=FALSE,
modelType="RM", bonf=FALSE,
estimation_param=
estimation_control(est="psychotools"))),
expected=3)})
# list of 3 is returned (item combinations, fit rasch model and ppar)
data(ADL)
firstrun <- exhaustiveRasch::test_waldtest(
items=c(6,7,12,14,15), dset=ADL, na.rm=TRUE, modelType="RM", bonf=FALSE,
estimation_param=
estimation_control(est="psychotools"))
testthat::test_that("test_waldtest: lowest p-value=0.519; pre-fit model
in the 'items' parameter",{
testthat::expect_equal(length(
exhaustiveRasch::test_waldtest(items=firstrun, dset=ADL, na.rm=TRUE,
modelType="RM", bonf=F,
estimation_param=
estimation_control(est="psychotools"))),
expected=3)})
# list of 3 is returned (item combinations, fit rasch model and ppar)
data(cognition)
testthat::test_that("test_waldtest: ",{
testthat::expect_equal(length(
exhaustiveRasch::test_waldtest(items=c(1:5,7), dset=cognition, na.rm=T,
modelType="PCM", bonf=FALSE, alpha=0.05,
icat=F, splitcr="random",
estimation_param=
estimation_control(est="pairwise",
splitseed=332))),
expected=3)})
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